Lecture Slides Elementary Statistics Tenth Edition and the

Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola Slide 1

Chapter 15 Projects, Procedures, Perspectives 15 -1 Projects 15 -2 Procedures 15 -3 Perspectives Slide 2

Section 15 -1 Projects Created by Erin Hodgess, Houston, Texas Revised to accompany 10 th Edition, Jim Zimmer, Chattanooga State, Chattanooga, TN Slide 3

Key Concept This section includes suggestions for a final project in the introductory statistics course. One fantastic advantage of this course is that it deals with skills and concepts that can be applied immediately to the real world. After only one semester, students are able to conduct their own studies. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 4

Projects v Group/Individual Topics can be assigned to individuals, but group projects are particularly effective because they help develop the interpersonal skills that are so necessary in today’s working environment. v Oral Report A 10 - to 15 -minute-long class presentation should involve all group members in a coordinated effort to clearly describe the important components of the study. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 5

Projects v Written Report A brief written report should include the following: 1. List of data collected along with description of how the data were obtained. 2. Description of the method of analysis. 3. Relevant graphs and/or statistics, including STATDISK, Minitab, Excel, or TI-83/84 displays. 4. Statement of conclusion. 5. Reasons why the results might not be correct, along with a description of ways in which the study could be improved, given sufficient time and money. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 6

Projects v Large Classes or Online Classes: Posters or Power. Point Some classes are too large for individual projects or group projects with three or four or five students per group. Some online classes are not able to meet as a group. For such cases, reports of individual or small group projects can be presented through posters or Power. Point presentations. v Surveys can be an excellent source of data. v Project Topic suggestions are listed in the text. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 7

Section 15 -2 Procedures Created by Erin Hodgess, Houston, Texas Revised to accompany 10 th Edition, Jim Zimmer, Chattanooga State, Chattanooga, TN Slide 8

Key Concept This section describes a general procedure for conducting a statistical analysis of data. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 9

Procedures v Exploring, Comparing, Describing After collecting data, address the following: 1. Center: Find the mean and median. 2. Variation: Find the range and standard deviation. 3. Distribution: Construct a histogram and a normal quantile plot. 4. Outliers: Identify any sample values that lie very far away from the vast majority of the others. 5. Time: Determine if the population is stable or if its characteristics are changing over time. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 10

Procedures v Inferences: Estimating Parameters and Hypothesis Testing Here are some key questions that should be answered: • What is the level of measurement (nominal, ordinal, interval, ratio) of the data? • Does the study involve one, two, or more populations? • What is the relevant parameter (mean, standard deviation, proportion)? • Is the population standard deviation known? • Is there reason to believe that the population is normally distributed? • What is the basic question or issue to address? Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 11

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Ordinal (such as data consisting of ranks) Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 12

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Two Populations More than Two Populations Chap. 12, 13 -5 Ordinal (such as data consisting of ranks) Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 13

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Variance Two Populations More than Two Populations Chap. 12, 13 -5 Ordinal (such as data consisting of ranks) Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 14

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Variance Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 Correlation, Regression Chap. 10, 13 -6 Ordinal (such as data consisting of ranks) Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 15

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Variance Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Correlation, Regression Chap. 10, 13 -6 Ordinal (such as data consisting of ranks) Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 16

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Variance Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 Correlation, Regression Chap. 10, 13 -6 Ordinal (such as data consisting of ranks) Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Hypothesis Testing: 8 -6 Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 17

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Ordinal (such as data consisting of ranks) Variance Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 One Population 13 -2 Correlation, Regression Chap. 10, 13 -6 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Two Populations More than Two Populations 13 -5 Hypothesis Testing: 8 -6 Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 18

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Ordinal (such as data consisting of ranks) Variance Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 One Population 13 -2 Two Populations More than Two Populations 13 -5 Correlation, Regression Chap. 10, 13 -6 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Independent: 13 -4 Matched Pairs: 13 -3 Hypothesis Testing: 8 -6 Nominal (data consisting of proportions or frequency counts for different categories) Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 19

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Ordinal (such as data consisting of ranks) Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 One Population 13 -2 Two Populations More than Two Populations 13 -5 Nominal (data consisting of proportions or frequency counts for different categories) Variance Correlation, Regression Chap. 10, 13 -6 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Independent: 13 -4 Matched Pairs: 13 -3 Hypothesis Testing: 8 -6 Frequency Counts for Categories Proportions Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 20

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Ordinal (such as data consisting of ranks) Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 One Population 13 -2 Two Populations More than Two Populations 13 -5 Nominal (data consisting of proportions or frequency counts for different categories) Variance Frequency Counts for Categories Correlation, Regression Chap. 10, 13 -6 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Independent: 13 -4 Matched Pairs: 13 -3 Hypothesis Testing: 8 -6 Multinomial (one row) 11 -2 Contingency Table (multiple rows, columns) 11 -3 Proportions Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 21

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Ordinal (such as data consisting of ranks) Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 One Population 13 -2 Two Populations More than Two Populations 13 -5 Nominal (data consisting of proportions or frequency counts for different categories) Variance Frequency Counts for Categories Proportions Correlation, Regression Chap. 10, 13 -6 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Independent: 13 -4 Matched Pairs: 13 -3 Hypothesis Testing: 8 -6 Multinomial (one row) 11 -2 Contingency Table (multiple rows, columns) 11 -3 Two Populations: 9 -2 One Population Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 22

FIGURE 15 -1 Selecting the Appropriate Procedure Level of Measurement Claim or Parameter Mean One Population Interval or Ratio (such as heights, weights) What is the level of measurement of the data? 1 -2 Number of Populations Ordinal (such as data consisting of ranks) Two Populations Means: 9 -3, 9 -4 More than Two Populations Chap. 12, 13 -5 Variances: 9 -5 One Population 13 -2 Two Populations More than Two Populations 13 -5 Nominal (data consisting of proportions or frequency counts for different categories) Variance Frequency Counts for Categories Proportions Correlation, Regression Chap. 10, 13 -6 Inference Estimating with Confidence Interval: 7 -3, 7 -4 Hypothesis Testing with Large Sample: 8 -4, 8 -5 Estimating with Confidence Interval: 7 -5 Independent: 13 -4 Matched Pairs: 13 -3 Hypothesis Testing: 8 -6 Multinomial (one row) 11 -2 Contingency Table (multiple rows, columns) 11 -3 Two Populations: 9 -2 One Population Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Estimating Proportion with Confidence Interval: 7 -2 Hypothesis Testing: 8 -3, 13 -2 Slide 23

Section 15 -3 Perspectives Created by Erin Hodgess, Houston, Texas Revised to accompany 10 th Edition, Jim Zimmer, Chattanooga State, Chattanooga, TN Slide 24

Key Concept No single introductory statistics course can transform anyone into an expert statistician. Know that professional help is available from expert statisticians, and this introductory statistics course will help you in discussions with one of these experts. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 25

Perspective v Successful completion of an introductory statistics course results in benefits far beyond the attainment of credit toward a college degree. • Improved job marketability • Ability to critically analyze reports in media and journals • Understanding of the basic concepts of probability and chance • Knowledge of importance of statistical procedures Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 26

Perspective v Remember that expert ability in analyzing statistics is of little value if good sampling techniques are not employed to develop the sample. v Although computers and calculators are good at yielding results, careful interpretation of the results are required. v Successful Completion of an introductory statistics course can enable students to grow as individuals and professionals and become people who are truly educated. Copyright © 2007 Pearson Education, Inc Publishing as Pearson Addison-Wesley. Slide 27